transform_schema() — anthropic-sdk-python Function Reference

Architecture documentation for the transform_schema() function in _transform.py from the anthropic-sdk-python codebase.

Function python AnthropicClient AsyncAPI

Entity Profile

AnthropicClient→ AsyncAPI→ transform_schema() — anthropic-sdk-python Function Reference

Dependency Diagram

graph TD
  18c66e29_88d3_b5f9_0448_f30338a098a7["transform_schema()"]
  69ef29cd_4eb8_35c9_a323_d7cf936be862["_transform.py"]
  18c66e29_88d3_b5f9_0448_f30338a098a7 -->|defined in| 69ef29cd_4eb8_35c9_a323_d7cf936be862
  style 18c66e29_88d3_b5f9_0448_f30338a098a7 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

src/anthropic/lib/_parse/_transform.py lines 54–167

def transform_schema(
    json_schema: type[pydantic.BaseModel] | dict[str, Any],
) -> dict[str, Any]:
    """
    Transforms a JSON schema to ensure it conforms to the API's expectations.

    Args:
        json_schema (Dict[str, Any]): The original JSON schema.

    Returns:
        The transformed JSON schema.

    Examples:
        >>> transform_schema(
        ...     {
        ...         "type": "integer",
        ...         "minimum": 1,
        ...         "maximum": 10,
        ...         "description": "A number",
        ...     }
        ... )
        {'type': 'integer', 'description': 'A number\n\n{minimum: 1, maximum: 10}'}
    """
    if inspect.isclass(json_schema) and issubclass(json_schema, pydantic.BaseModel):  # pyright: ignore[reportUnnecessaryIsInstance]
        json_schema = json_schema.model_json_schema()

    strict_schema: dict[str, Any] = {}
    json_schema = {**json_schema}

    ref = json_schema.pop("$ref", None)
    if ref is not None:
        strict_schema["$ref"] = ref
        return strict_schema

    defs = json_schema.pop("$defs", None)
    if defs is not None:
        strict_defs: dict[str, Any] = {}
        strict_schema["$defs"] = strict_defs

        for name, schema in defs.items():
            strict_defs[name] = transform_schema(schema)

    type_: Optional[SupportedTypes] = json_schema.pop("type", None)
    any_of = json_schema.pop("anyOf", None)
    one_of = json_schema.pop("oneOf", None)
    all_of = json_schema.pop("allOf", None)

    if is_list(any_of):
        strict_schema["anyOf"] = [transform_schema(cast("dict[str, Any]", variant)) for variant in any_of]
    elif is_list(one_of):
        strict_schema["anyOf"] = [transform_schema(cast("dict[str, Any]", variant)) for variant in one_of]
    elif is_list(all_of):
        strict_schema["allOf"] = [transform_schema(cast("dict[str, Any]", variant)) for variant in all_of]
    else:
        if type_ is None:
            raise ValueError("Schema must have a 'type', 'anyOf', 'oneOf', or 'allOf' field.")

        strict_schema["type"] = type_

    description = json_schema.pop("description", None)
    if description is not None:
        strict_schema["description"] = description

    title = json_schema.pop("title", None)
    if title is not None:
        strict_schema["title"] = title

    if type_ == "object":
        strict_schema["properties"] = {
            key: transform_schema(prop_schema) for key, prop_schema in json_schema.pop("properties", {}).items()
        }
        json_schema.pop("additionalProperties", None)
        strict_schema["additionalProperties"] = False

        required = json_schema.pop("required", None)
        if required is not None:
            strict_schema["required"] = required

    elif type_ == "string":
        format = json_schema.pop("format", None)
        if format and format in SupportedStringFormats: